In this work we apply the new noise reduction method for the enhancement of the images of gene chips. We demonstrate that the new technique is capable of reducing various kinds of noise present in microarray images an...
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Software cybernetics explores the interplay between software and control and is motivated by the fundamental question whether or not and how software behavior can be controlled. In this paper, we formulate the underly...
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Software cybernetics explores the interplay between software and control and is motivated by the fundamental question whether or not and how software behavior can be controlled. In this paper, we formulate the underlying motivations and ideas of software cybernetics and review various existing research topics in this emerging area, including feedback mechanisms in software processes, bisimulation and controllability, adaptive software, software synthesis, software test process control, and adaptive testing. We identify software rejuvenation and performance control, software fault-tolerance, logical foundation for control systems, and communication complexity for control systems as potential research topics. Several on-going research projects are also summarized.
Availability of large full-text document collections in electronic form has created a need for tools and techniques that assist users in organizing these collections. Document clustering is one of the popular methods ...
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Availability of large full-text document collections in electronic form has created a need for tools and techniques that assist users in organizing these collections. Document clustering is one of the popular methods used for this purpose. In this paper, we propose the neural network based document clustering method by using a hierarchically organized network built up from independent Self-Organizing Map (SOM) and Adaptive Resonance Theory (ART) neural networks. We present clustering results using the REUTERS corpus and show an improvement in clustering performance using both entropy and F-measure as evaluation measures.
This paper describes a design experience of a low-cost 6 DOF spatial tracker system where relative low accuracy and relatively long ranges, wireless communication will be achieved by means of low cost accelerometers a...
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ISBN:
(纸本)0780377850
This paper describes a design experience of a low-cost 6 DOF spatial tracker system where relative low accuracy and relatively long ranges, wireless communication will be achieved by means of low cost accelerometers and gyros with contemporary microprocessor. However, there are two key problems; one is the bias drift problem and the other is the single and double integration of acceleration signal suffers not only from noise but also from nonlinear effects caused by gravity. Several algorithms are proposed to cope with such problems, and verified by some successful experimental results.
In this paper, we provide and analyze a sigmoidal optimization of a recently developed class of weighted vector directional filters (WVDFs) outputting the input multichannel sample associated with the minimum sum of w...
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A control systems engineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detai...
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In this paper a novel approach to the problem of impulsive noise reduction in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the max...
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In this paper a novel approach to the problem of impulsive noise reduction in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The new method is faster than the standard vector median filter (VMF) and preserves better edges and fine image details. Simulation results show that the proposed method outperforms standard algorithms of the reduction of impulsive noise in color images.
In this paper a new method of impulsive noise reduction in microarray images is presented. The new technique is capable of attenuating impulsive noise, while preserving the sharpness of the image edges. Extensive simu...
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In this paper, a vector generalization of weighted median optimization approaches is provided. The proposed optimized weighted vector median filters utilize the relationship between standard median filter and vector m...
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In this paper a new robust steepest-descent algorithm for discrete-time iterative learning control is introduced for plant models with multiplicative uncertainty. A theoretical analysis of the algorithm shows that if ...
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In this paper a new robust steepest-descent algorithm for discrete-time iterative learning control is introduced for plant models with multiplicative uncertainty. A theoretical analysis of the algorithm shows that if a tuning parameter in the algorithm is selected to be sufficiently large, the algorithm will result in monotonic convergence if the plant uncertainty satisfies a positivity condition. This is a major improvement when compared to the standard steepest-descent algorithm, which lacks a mechanism for finding a balance between convergence speed and robustness. Experimental work on a gantry robot is performed to demonstrate that the algorithm results in near perfect tracking in the limit.
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